Update on the management of acute pancreatitis
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review provides insight into the recent advancements in the management of acute pancreatitis. RECENT FINDINGS: Moderate fluid resuscitation and Ringer's lactate has advantages above aggressive fluid resuscitation and normal saline, respectively. A normal "on-demand" diet has a positive effect on recovery from acute pancreatitis and length of hospital stay. A multimodal pain management approach including epidural analgesia might reduce unwarranted effects of opiate use. A more targeted use of antibiotics is starting to emerge. Markers such as procalcitonin may be used to limit unwarranted antibiotic use. Conversely, many patients with infected necrotizing pancreatitis can be treated with only antibiotics, although the optimal choice and duration is unclear. Delay of drainage as much as is possible is advised since it is associated with less procedures. If drainage is required, clinicians have an expanding arsenal of interventional options to their disposal such as the lumen-apposing metal stent for transgastric drainage and (repeated) necrosectomy. Immunomodulation using removal of systemic cytokines or anti-inflammatory drugs is an attractive idea, but up to now the results of clinical trials are disappointing. No additional preventive measures beside non-steroidal anti-inflammatory drugs (NSAIDs) can be recommended for post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis. SUMMARY: More treatment modalities that are less invasive became available and a trend towards less aggressive treatments (fluids, starvation, interventions, opiates) of acute pancreatitis is again emerging. Despite recent advancements, the pathophysiology of specific subgroup phenotypes is still poorly understood which reflects the disappointing results of pharmacological and immunomodulatory trials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".